本文選題：社會網(wǎng)絡(luò) + 競爭影響最大化��； 參考：《云南大學(xué)》2016年博士論文

【摘要】：隨著在線社交網(wǎng)絡(luò)的流行,社會網(wǎng)絡(luò)影響傳播引起很多研究者的關(guān)注,社會網(wǎng)絡(luò)影響傳播最大化是社會網(wǎng)絡(luò)影響傳播的關(guān)鍵問題之一。社會網(wǎng)絡(luò)影響傳播最大化是指給定一個社會網(wǎng)絡(luò)、傳播模型和種子節(jié)點(diǎn)個數(shù),找到指定個數(shù)的種子節(jié)點(diǎn)集合,使得影響通過這個種子節(jié)點(diǎn)集合傳播最大化。社會網(wǎng)絡(luò)影響傳播最大化在病毒式營銷和信息的傳播等方面具有重要應(yīng)用。在病毒式營銷和信息的傳播中,不僅存在單一的影響傳播,還存在競爭和合作影響傳播。本文針對社會網(wǎng)絡(luò)中病毒式營銷和信息傳播的應(yīng)用背景,研究了社會網(wǎng)絡(luò)中競爭與合作影響最大化,并用實(shí)驗(yàn)驗(yàn)證了本文方法的可行性和有效性。本文的主要工作和創(chuàng)新之處總結(jié)如下：●研究了社會網(wǎng)絡(luò)影響傳播中種子選擇的并行方法。本文基于候選殼生成、熱擴(kuò)散模型及候選殼影響最大化的基本思想,提出了基于候選殼的并行選取種子節(jié)點(diǎn)集合最大化社會網(wǎng)絡(luò)影響傳播方法。該研究以提高選取種子的速度為出發(fā)點(diǎn),基于候選殼,可并行地在候選殼中選取種子節(jié)點(diǎn)集合；基于熱擴(kuò)散模型模擬病毒式營銷中影響的傳播,引入時間參數(shù),從而更好地模擬病毒式營銷中影響的傳播。●研究了面向病毒式營銷的社會網(wǎng)絡(luò)競爭影響最大化。本文基于擴(kuò)展線性閾值模型、子模性分析框架及貪心法的基本思想,提出了病毒式營銷中競爭影響傳播最大化的方法。該研究以社會網(wǎng)絡(luò)的實(shí)際應(yīng)用為出發(fā)點(diǎn),基于擴(kuò)展線性閾值模型模擬競爭影響傳播,從而更符合實(shí)際地模擬病毒式營銷中的競爭影響傳播；基于子模性的分析框架,為貪心法近似地選取種子節(jié)點(diǎn)集合提供了理論保證�！裱芯苛嗣嫦蛐畔鞑サ纳鐣W(wǎng)絡(luò)競爭影響最大化。本文基于可能圖、競爭影響傳播模型、子模性分析框架和貪心法改進(jìn)算法的基本思想,提出了信息傳播中競爭影響最大化的方法。該研究以可能圖為出發(fā)點(diǎn),大大消除了計(jì)算的難度,提高了選取種子節(jié)點(diǎn)集合的速度；采用競爭影響傳播模型來模擬可能圖中的競爭影響傳播過程：基于子模性的分析框架,從而可以采用花費(fèi)有效的懶惰向前算法來近似地選取種子節(jié)點(diǎn)集合,花費(fèi)有效的懶惰向前算法是一種貪心法的加速算法�！裱芯苛嗣嫦虿《臼綘I銷的合作影響傳播最大化。以模擬病毒式營銷中商品的合作促銷為目的,本文基于相似度模型、合作影響傳播圖、帶接受概率的獨(dú)立級聯(lián)模型和改進(jìn)的貪心算法的基本思想,提出了病毒式營銷中合作影響傳播最大化的方法。該研究以面向病毒式營銷的合作影響傳播最大化為出發(fā)點(diǎn)�；趩为�(dú)一種商品的影響傳播圖及關(guān)聯(lián)規(guī)則生成合作影響傳播圖；采用帶接受概率的獨(dú)立級聯(lián)模型來更符合實(shí)際地模擬病毒式營銷中合作影響傳播過程；提出改進(jìn)的貪心法來有效地選取種子節(jié)點(diǎn)集合,避免了大量的蒙特卡洛模擬計(jì)算。
[Abstract]:With the popularity of online social networks, social network impact communication has attracted many researchers' attention. The maximization of social network impact communication is one of the key issues of social network impact communication. The maximization of social network influence propagation means that given a social network, the propagation model and the number of seed nodes, the set of seed nodes is found to maximize the propagation of influence through the set of seed nodes. The social network influence communication maximization has the important application in the virus marketing and the information dissemination and so on. In viral marketing and information dissemination, there is not only a single impact of communication, but also competition and cooperation. Aiming at the application background of viral marketing and information dissemination in social network, this paper studies the maximization of the influence of competition and cooperation in social network, and verifies the feasibility and effectiveness of this method by experiments. The main work and innovations of this paper are summarized as follows: the parallel methods of seed selection in social network influence propagation are studied. Based on candidate shell generation, thermal diffusion model and the basic idea of maximizing the impact of candidate shells, this paper proposes a parallel selection of seed node sets based on candidate shells to maximize the social network impact propagation method. Based on the candidate shell, the seed node set can be selected in parallel, based on the thermal diffusion model to simulate the spread of the influence in viral marketing, and the time parameter is introduced. In order to better simulate the spread of influence in viral marketing, this paper studies the maximization of the impact of social network competition for viral marketing. Based on the extended linear threshold model, the submodule analysis framework and the greedy method, this paper proposes a method to maximize the spread of competitive influence in viral marketing. This study takes the practical application of social network as the starting point and simulates the spread of competition influence based on extended linear threshold model, which is more in line with the actual simulation of competition impact propagation in viral marketing, and based on the analysis framework of submodule. It provides a theoretical guarantee for the greedy method to select the seed node set approximately, and studies the maximization of the competitive impact of the social network oriented to information dissemination. Based on the basic ideas of possibility graph, competition influence propagation model, submodule analysis framework and greedy method, this paper proposes a method to maximize the influence of competition in information dissemination. In this study, the difficulty of calculation is greatly eliminated, and the speed of selecting seed nodes is improved. The competitive influence propagation model is used to simulate the process of competition influence propagation in the possible graph: an analysis framework based on submodule. Therefore, the cost effective lazy forward algorithm can be used to approximate select the seed node set. The cost effective lazy forward algorithm is an accelerated algorithm of greedy method. For the purpose of simulating cooperative promotion of merchandise in viral marketing, this paper bases on similarity model, cooperative influence propagation graph, independent cascade model with acceptance probability and improved greedy algorithm. This paper puts forward the method of maximizing the influence of cooperation in viral marketing. This study is based on the cooperative impact of viral marketing on communication maximization. Based on the influence propagation diagram and association rules of a single commodity, the cooperative impact propagation map is generated, and the independent cascade model with acceptance probability is used to simulate the process of cooperative influence propagation in viral marketing more accurately. An improved greedy method is proposed to select seed nodes effectively, avoiding a large number of Monte Carlo simulations.
【學(xué)位授予單位】：云南大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2016
【分類號】：G206;TP393.09

【參考文獻(xiàn)】

相關(guān)期刊論文 前4條

1 曹玖新;董丹;徐順;鄭嘯;劉波;羅軍舟;;一種基于k-核的社會網(wǎng)絡(luò)影響最大化算法[J];計(jì)算機(jī)學(xué)報;2015年02期

2 吳信東;李毅;李磊;;在線社交網(wǎng)絡(luò)影響力分析[J];計(jì)算機(jī)學(xué)報;2014年04期

3 李棟;徐志明;李生;劉挺;王秀文;;在線社會網(wǎng)絡(luò)中信息擴(kuò)散[J];計(jì)算機(jī)學(xué)報;2014年01期

4 任卓明;劉建國;邵鳳;胡兆龍;郭強(qiáng);;復(fù)雜網(wǎng)絡(luò)中最小K-核節(jié)點(diǎn)的傳播能力分析[J];物理學(xué)報;2013年10期

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